Looking inward to the use of unmanned aerial vehicle(UAV) for rice production assesment in Indonesia.
Looking Inward to the Use of Unmanned Aerial Vehicle (UAV)
for Rice Production Assessment in Indonesia
14
Ambarawati ,
34
Wijaya ,
I Gusti Agung Ayu
Chiharu
I Made Anom Sutrisna
4
54
Anak Agung Sagung Putri Komaladara , Anak Agung Ayu Mirah Adi
UDAYANA UNIVERSITY
1Faculty
24
Hongo ,
of Agriculture, Udayana University, Indonesia, 2Center for Environmental Remote Sensing (CEReS), Chiba University, Japan, 3Faculty of Agricultural Technology, Udayana University, Indonesia,
4Center on Food Availability for Sustainable Improvement (CFASI), Udayana University, Indonesia, 5Faculty of Veterinary Medicine, Udayana University, Indonesia
Abstract
Objectives
Rice is the main source of carbohydrate for most Indonesians. Rice production has been very dynamic due to
improved infrastructure, research and development, and better farm management. However, rice production is
susceptible to loss caused by drought, pest and disease attack and climate change. With the growing concern
on sustainable and self-reliance food production in the country, there is an urgency to encourage research and
efforts to increase rice productivity. Attempts to provide spatial distribution of rice fields on high resolution
optical remote sensing data have been employed to some extent, however this technology could be costly. The
use of UAV has been introduced to estimate damage ratio in rice crop recently in Indonesia. This technology is
one of the ways to estimate rice production faster, cost saving and before harvesting time. This study aims to
provide spatio temporal and damage ratio of rice crop using UAV in Indonesia. The study empirically presents
the use of UAV (Phantom 2 Vision +) on rice fields to the state condition and development of management
zone map in Bali as an example. The study concludes that the use of UAV allows researchers to pin point
characteristics of crop and land in a specific area of a farm. This will then allow researchers to assist farmers in
implementing specific and appropriate solutions to production issues.
This study aims to provide rice farming condition on a far er’s group and spatio temporal of rice crop using UAV
in Indonesia. The study empirically presents the use of UAV (Phantom 2 Vision +) on rice fields to capture the
existing condition and development of management zone map in Bali as an example.
Key words: UAV, rice production, damage ratio
Background
Rice is the most important source of carbohydrate for most Indonesians, cultivated widely throughout the
country. Rice production has been fluctuating for the last five years depending on several factors including
harvested area and yield. At average, rice production tends to slightly decrease from 71.28 million tons in 2013
to 70.85 million tons in 2014, a decrease of 0.60 percent. The average yield of rice production for the whole
country is 5.3 t ha-1. Regarding food security management, the Indonesian government concerns on monitoring
and utilizing improved technologies those are available for sustainable rice production. A number of research
and development (R&D) has been carried out to portray the dynamics of rice production in Indonesia. These
are including the use of remote sensing and Geographical Information System (GIS) techniques (Uchida 2010,
Nuarsa et al. 2011). Despite the advantage use of remote sensing technology, the method could be constrained
by high cost for the images as well as the time for ordering images. The use of UAV has been applied in several
places in Indonesia for small area mapping (Sadikin et al. 2014).
The island of Bali was selected in this study to provide
spatial land data with the low cost of photogrammetric
method of UAV. Bali province account for only 0.29
percent of the total area of Indonesia, however it is
worldwide known for its tourist destination. The tourist
sector contributes more than 70 percent to the regional
domestic product. On the other hand, agricultural sector
including rice production still plays an important role in the
Bali economy because of its 20 percent contribution. The
Bali government has vision to achieve resilient agriculture
in a sense of advancement, safe, peaceful, and wealth,
called the MANDARA program. The mission is to achieve
self-reliant food through empowerment of agricultural
resources optimally and sustainably. This mission includes
increasing far er’s income for better livelihood.
The common cropping pattern in a year is rice – rice – secondary crops. Depending on water availability,
farmers in most places in Bali are able to plant paddy twice in a year and during dry season they plant
secondary crops such as corn and soybeans. With the average yield of 5.8 ton/ha, there is rice production
864,200 ton/year. However, rice production in Bali is susceptible to failure not just because of drought and
pest and disease attack, but also from the climate change. Several efforts are contributable to this rice
production including innovative technology and improved agricultural practices. Concerning the exposure
risks, the use of imagery technology such as UAV is valuable to monitor the condition of plant and land
surface.
Results from farmer surveyed can be used as ground data
base for monitoring rice production in the area,
particularly on the implementation of good agricultural
practices. The data also indicate that rice production is
prone to failure mainly due to pests and diseases attack,
water shortage and climate change.
2. The UAV imagery result
Methodology
Results from the UAV imagery are presented in Figure 4 to
6. The images are able to capture the existing condition of
rice field at the selected area. The state of rice fields for
harvesting are seen clearly from different color of the
images. This information will ease the head of far er’s
group to collect tax from the selling yield. Taxes from rice
selling are agreed upon the farmer members to pay for
the function ceremony based on Hindu ritual and tertiary
flow maintenance of the water irrigation. Combination
from the ground data base and UAV images can be used
for the implementation of precision agriculture on the
area. At glance, damage ratio from these fields cannot be
calculated yet due to the image results however the
images show the condition of farm are good, showing less
pest and disease attack. Further analysis is required to
correlate between aerial images with the ground data to
be effective in mapping the selected area.
Study location: Subak Cemagi Let, Cemagi village, Mengwi
district, regency of Badung, Bali. Subak Cemagi is the largest
far er’s group at Cemagi village with the area of paddy field of
324 ha. The location was selected purposively in the sense that
agricultural sector may be left for other employment
opportunities in the tourist sector. Cemagi village lies on
longitude 115o06’45.3” E and latitude 8o37”49.6”S.
Data collection: There were two steps carried out in this study.
First, fifty farmers were interviewed randomly in October 2014
to find out their rice yield using ubinan system (2.5 m x 2.5 m of
harvested samples) and obstacles related to rice production.
Each farmer location was recorded to be used for data base. This
provided insights on the far er’s rice production and hindrance
on paddy field. Secondly, UAV Phantom 2 Vision + was used to
map paddy field at Subak Cemagi in October 2015 representing
small area and possibility to calculate damage ratio. The flying
height was 50 meter with 3 seconds interval. The combination of
the two steps allows researchers to pin point characteristics of
paddy field in a specific area of a farm.
Figure 1. Phanthom 2 Vision +
Results and Discussion
The use of UAV imagery is not without drawback. It has to
be concerned with the time to get rid of cloud effect and
height of flying to capture the best picture. The images
taken could be also overlapped. The post process of each
photograph is required to portray land parcels image.
Accordingly, it should be taken into consideration when
conducting data analysis.
Figure 4. Image of Subak Cemagi Let using UAV
Phantom 2 Version +
Figure 5. Different position of UAV standing
point results in different image
Figure 6. UAV image capturing different state of
plant condition
Conclusion
1. Farmer survey
Farmers at the location of study carry out seed planting according to the schedule agreed by the members of
farmer group on a regular subak meeting. This schedule supports harvesting time to estimate rice production
on the field. Farmers are categorized as small-scale farm as the average of land holding at 0.32 ha, ranging from
0.09 to 0.8 ha. Looking at the distribution, 40 percent of farmers hold below than 0.20 ha of paddy field, while
only 10 percent of farmers have more than 0.5 ha of land. This condition might affect the efficiency of the rice
production.
With regards to the rice yield, farmers were able to
achieve at the average of 8.57 ton ha-1. Rice
productivity in Cemagi village was much higher than
that of the average of rice production in Bali, which was
5.8 ton ha-1 (Bali Board of Statistics, 2014).There was
more than half farmers could achieve above the
average of productivity (Figure 2). There was only 5
percent of farmers in Mengwi village produced 5.4 ton
ha-1.
Figure 3 indicates that pest and disease attack remain
to be a major cause of crop failure. This is followed by
water scarcity and climate change. Farmers claim that
the drought caused by climate change force them to
shift in their planting schedules, which may jeopardize
the regio ’s food security.
Results from the UAV imagery is able to capture the existing condition of rice field at the small area. This
information reduces time to inspect for the state of rice fields. Correlation with the ground data allows
researchers to do further analysis for the implementation of precision agriculture. The drawback of the UAV use
could be overcome in the near future from the UAV design.
References:
Nuarsa, I W., Nisho, F. and Hongo, C. (2011). Relationship between rice spectral and rice yield. Journal of Agricultural Sciences, Vol 3
(2), 80-88.
Sadikin, H, Saptari, A.Y., Addulharis, R. And Hernandi, A. (2014). UAV system with terrestrial geo-referencing for small area mapping.
Presented in FIG Congress 2014, Engaging the Challenges-Enhancing the Relevance, Kuala Lumpur, Malaysia, 16-21 June, 2014.
Figure 2. Far ers’ ri e yield distri utio at Cemagi Village
Figure 3. Common causes of rice production failure in
Cemagi Village
Uchida, S. (2010). Monitoring of planting paddy rice with complex cropping pattern in the tropical humid climate region using Landsat
and Modis Data, A case of West Java, Indonesia. International Archives of the Photogrammetry, Remote Sensing and Spatial
Information Science, Volume XXXVIII, Part 8, Kyoto Japan.
Acknowledgements:
The authors would like to thank Udayana University and Chiba University for supporting this study. The authors would also like to
express their gratitude to the BPP Mengwi agricultural extension workers for coordinating the survey data collection.
Corresponding Author:
I Gusti Agung Ayu Ambarawati
annie_ambarawati@unud.ac.id
for Rice Production Assessment in Indonesia
14
Ambarawati ,
34
Wijaya ,
I Gusti Agung Ayu
Chiharu
I Made Anom Sutrisna
4
54
Anak Agung Sagung Putri Komaladara , Anak Agung Ayu Mirah Adi
UDAYANA UNIVERSITY
1Faculty
24
Hongo ,
of Agriculture, Udayana University, Indonesia, 2Center for Environmental Remote Sensing (CEReS), Chiba University, Japan, 3Faculty of Agricultural Technology, Udayana University, Indonesia,
4Center on Food Availability for Sustainable Improvement (CFASI), Udayana University, Indonesia, 5Faculty of Veterinary Medicine, Udayana University, Indonesia
Abstract
Objectives
Rice is the main source of carbohydrate for most Indonesians. Rice production has been very dynamic due to
improved infrastructure, research and development, and better farm management. However, rice production is
susceptible to loss caused by drought, pest and disease attack and climate change. With the growing concern
on sustainable and self-reliance food production in the country, there is an urgency to encourage research and
efforts to increase rice productivity. Attempts to provide spatial distribution of rice fields on high resolution
optical remote sensing data have been employed to some extent, however this technology could be costly. The
use of UAV has been introduced to estimate damage ratio in rice crop recently in Indonesia. This technology is
one of the ways to estimate rice production faster, cost saving and before harvesting time. This study aims to
provide spatio temporal and damage ratio of rice crop using UAV in Indonesia. The study empirically presents
the use of UAV (Phantom 2 Vision +) on rice fields to the state condition and development of management
zone map in Bali as an example. The study concludes that the use of UAV allows researchers to pin point
characteristics of crop and land in a specific area of a farm. This will then allow researchers to assist farmers in
implementing specific and appropriate solutions to production issues.
This study aims to provide rice farming condition on a far er’s group and spatio temporal of rice crop using UAV
in Indonesia. The study empirically presents the use of UAV (Phantom 2 Vision +) on rice fields to capture the
existing condition and development of management zone map in Bali as an example.
Key words: UAV, rice production, damage ratio
Background
Rice is the most important source of carbohydrate for most Indonesians, cultivated widely throughout the
country. Rice production has been fluctuating for the last five years depending on several factors including
harvested area and yield. At average, rice production tends to slightly decrease from 71.28 million tons in 2013
to 70.85 million tons in 2014, a decrease of 0.60 percent. The average yield of rice production for the whole
country is 5.3 t ha-1. Regarding food security management, the Indonesian government concerns on monitoring
and utilizing improved technologies those are available for sustainable rice production. A number of research
and development (R&D) has been carried out to portray the dynamics of rice production in Indonesia. These
are including the use of remote sensing and Geographical Information System (GIS) techniques (Uchida 2010,
Nuarsa et al. 2011). Despite the advantage use of remote sensing technology, the method could be constrained
by high cost for the images as well as the time for ordering images. The use of UAV has been applied in several
places in Indonesia for small area mapping (Sadikin et al. 2014).
The island of Bali was selected in this study to provide
spatial land data with the low cost of photogrammetric
method of UAV. Bali province account for only 0.29
percent of the total area of Indonesia, however it is
worldwide known for its tourist destination. The tourist
sector contributes more than 70 percent to the regional
domestic product. On the other hand, agricultural sector
including rice production still plays an important role in the
Bali economy because of its 20 percent contribution. The
Bali government has vision to achieve resilient agriculture
in a sense of advancement, safe, peaceful, and wealth,
called the MANDARA program. The mission is to achieve
self-reliant food through empowerment of agricultural
resources optimally and sustainably. This mission includes
increasing far er’s income for better livelihood.
The common cropping pattern in a year is rice – rice – secondary crops. Depending on water availability,
farmers in most places in Bali are able to plant paddy twice in a year and during dry season they plant
secondary crops such as corn and soybeans. With the average yield of 5.8 ton/ha, there is rice production
864,200 ton/year. However, rice production in Bali is susceptible to failure not just because of drought and
pest and disease attack, but also from the climate change. Several efforts are contributable to this rice
production including innovative technology and improved agricultural practices. Concerning the exposure
risks, the use of imagery technology such as UAV is valuable to monitor the condition of plant and land
surface.
Results from farmer surveyed can be used as ground data
base for monitoring rice production in the area,
particularly on the implementation of good agricultural
practices. The data also indicate that rice production is
prone to failure mainly due to pests and diseases attack,
water shortage and climate change.
2. The UAV imagery result
Methodology
Results from the UAV imagery are presented in Figure 4 to
6. The images are able to capture the existing condition of
rice field at the selected area. The state of rice fields for
harvesting are seen clearly from different color of the
images. This information will ease the head of far er’s
group to collect tax from the selling yield. Taxes from rice
selling are agreed upon the farmer members to pay for
the function ceremony based on Hindu ritual and tertiary
flow maintenance of the water irrigation. Combination
from the ground data base and UAV images can be used
for the implementation of precision agriculture on the
area. At glance, damage ratio from these fields cannot be
calculated yet due to the image results however the
images show the condition of farm are good, showing less
pest and disease attack. Further analysis is required to
correlate between aerial images with the ground data to
be effective in mapping the selected area.
Study location: Subak Cemagi Let, Cemagi village, Mengwi
district, regency of Badung, Bali. Subak Cemagi is the largest
far er’s group at Cemagi village with the area of paddy field of
324 ha. The location was selected purposively in the sense that
agricultural sector may be left for other employment
opportunities in the tourist sector. Cemagi village lies on
longitude 115o06’45.3” E and latitude 8o37”49.6”S.
Data collection: There were two steps carried out in this study.
First, fifty farmers were interviewed randomly in October 2014
to find out their rice yield using ubinan system (2.5 m x 2.5 m of
harvested samples) and obstacles related to rice production.
Each farmer location was recorded to be used for data base. This
provided insights on the far er’s rice production and hindrance
on paddy field. Secondly, UAV Phantom 2 Vision + was used to
map paddy field at Subak Cemagi in October 2015 representing
small area and possibility to calculate damage ratio. The flying
height was 50 meter with 3 seconds interval. The combination of
the two steps allows researchers to pin point characteristics of
paddy field in a specific area of a farm.
Figure 1. Phanthom 2 Vision +
Results and Discussion
The use of UAV imagery is not without drawback. It has to
be concerned with the time to get rid of cloud effect and
height of flying to capture the best picture. The images
taken could be also overlapped. The post process of each
photograph is required to portray land parcels image.
Accordingly, it should be taken into consideration when
conducting data analysis.
Figure 4. Image of Subak Cemagi Let using UAV
Phantom 2 Version +
Figure 5. Different position of UAV standing
point results in different image
Figure 6. UAV image capturing different state of
plant condition
Conclusion
1. Farmer survey
Farmers at the location of study carry out seed planting according to the schedule agreed by the members of
farmer group on a regular subak meeting. This schedule supports harvesting time to estimate rice production
on the field. Farmers are categorized as small-scale farm as the average of land holding at 0.32 ha, ranging from
0.09 to 0.8 ha. Looking at the distribution, 40 percent of farmers hold below than 0.20 ha of paddy field, while
only 10 percent of farmers have more than 0.5 ha of land. This condition might affect the efficiency of the rice
production.
With regards to the rice yield, farmers were able to
achieve at the average of 8.57 ton ha-1. Rice
productivity in Cemagi village was much higher than
that of the average of rice production in Bali, which was
5.8 ton ha-1 (Bali Board of Statistics, 2014).There was
more than half farmers could achieve above the
average of productivity (Figure 2). There was only 5
percent of farmers in Mengwi village produced 5.4 ton
ha-1.
Figure 3 indicates that pest and disease attack remain
to be a major cause of crop failure. This is followed by
water scarcity and climate change. Farmers claim that
the drought caused by climate change force them to
shift in their planting schedules, which may jeopardize
the regio ’s food security.
Results from the UAV imagery is able to capture the existing condition of rice field at the small area. This
information reduces time to inspect for the state of rice fields. Correlation with the ground data allows
researchers to do further analysis for the implementation of precision agriculture. The drawback of the UAV use
could be overcome in the near future from the UAV design.
References:
Nuarsa, I W., Nisho, F. and Hongo, C. (2011). Relationship between rice spectral and rice yield. Journal of Agricultural Sciences, Vol 3
(2), 80-88.
Sadikin, H, Saptari, A.Y., Addulharis, R. And Hernandi, A. (2014). UAV system with terrestrial geo-referencing for small area mapping.
Presented in FIG Congress 2014, Engaging the Challenges-Enhancing the Relevance, Kuala Lumpur, Malaysia, 16-21 June, 2014.
Figure 2. Far ers’ ri e yield distri utio at Cemagi Village
Figure 3. Common causes of rice production failure in
Cemagi Village
Uchida, S. (2010). Monitoring of planting paddy rice with complex cropping pattern in the tropical humid climate region using Landsat
and Modis Data, A case of West Java, Indonesia. International Archives of the Photogrammetry, Remote Sensing and Spatial
Information Science, Volume XXXVIII, Part 8, Kyoto Japan.
Acknowledgements:
The authors would like to thank Udayana University and Chiba University for supporting this study. The authors would also like to
express their gratitude to the BPP Mengwi agricultural extension workers for coordinating the survey data collection.
Corresponding Author:
I Gusti Agung Ayu Ambarawati
annie_ambarawati@unud.ac.id